People Programs and Total Rewards Architect

LangChain LangChain · Data AI · San Francisco, CA · People

This role is for a People Programs and Total Rewards Architect at LangChain, a company focused on making intelligent agents ubiquitous. The role involves building and operationalizing how LangChain rewards, recognizes, and retains talent, with a strong emphasis on integrating AI agents and LLM-driven workflows into People Programs and Total Rewards. The architect will design compensation philosophies, equity strategies, and performance programs, and will partner with the Applied AI team to explore how AI-augmented roles impact performance and upskilling. The role requires a product mindset, quantitative rigor, and AI fluency to leverage AI tools for automating tactical HR tasks and focusing on strategic initiatives.

What you'd actually do

  1. Design and deploy a global compensation philosophy from first principles. You’ll build the frameworks for salary bands, leveling, and promotion guidelines that stay ahead of the hyper-competitive AI talent market.
  2. Lead the charge in integrating AI agents and LLM-driven workflows into People Programs and Total Rewards. Your goal is to automate and leverage agents to handle the tactical (internal FAQs, synthesizing performance feedback, building job architecture) so you can focus on the complex underlying strategy, philosophy, and change management. Use our own tech stack to automate the "ops" out of People Ops.
  3. Partner with our Applied AI team to drive company-wide adoption of AI tools, rethinking how AI-augmented roles change our definitions of performance, upskilling, and career velocity.
  4. Own the evolution of our global equity programs. You’ll manage forecasting and modeling while ensuring every LangChain team member deeply understands the value of their stake in our mission.
  5. Design and run high-velocity performance and development programs that emphasize impact over activity, ensuring talent density remains elite as we scale.

Skills

Required

  • 6-10+ Years of Building People programs or Total Rewards at a high-growth tech startup
  • Extreme Agency: comfortable in the messy middle of hyper-growth and can navigate ambiguity with a technical mindset
  • AI Fluency: understand how to leverage agents, prompt engineering, and automation
  • Quantitative Rigor: compensation modeling, data visualization, and financial discipline
  • Product Mindset: approach People programs with a "version 1.0 vs. version 2.0" mentality
  • Global Mindset: built for distributed teams and understand the nuances of designing for a global workforce
  • Radical Clarity: translate complex models into understandable communication
  • Systems Thinking vs. Rigid Rules: understand how changes impact various business areas
  • High EQ + Low Ego: handle sensitive data with discretion and act as a neutral, trusted advisor
  • Conflict as a Catalyst: use data and empathy to drive to a fair resolution

What the JD emphasized

  • hyper-competitive AI talent market
  • AI agents and LLM-driven workflows
  • AI-augmented roles
  • AI fluency
  • leverage agents, prompt engineering, and automation